R/RcppExports.R

In danheck/MCMCprec: Precision of Discrete Parameters in Transdimensional MCMC

# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

inv_digamma <- function(y, iter = 5L) {
    .Call(`_MCMCprecision_inv_digamma`, y, iter)
}

dirichlet_fp <- function(alpha, logx_mean, maxit = 1e5L, abstol = 1e-5) {
    .Call(`_MCMCprecision_dirichlet_fp`, alpha, logx_mean, maxit, abstol)
}

sim_mc <- function(n, P, start) {
    .Call(`_MCMCprecision_sim_mc`, n, P, start)
}

rdirichletPt <- function(Pt) {
    .Call(`_MCMCprecision_rdirichletPt`, Pt)
}

getP2 <- function(P, pi) {
    .Call(`_MCMCprecision_getP2`, P, pi)
}

postpred <- function(P, pi, N2) {
    .Call(`_MCMCprecision_postpred`, P, pi, N2)
}

stationaryArma <- function(N, epsilon = 0, sample = 5000L, progress = TRUE, digits = 8.) {
    .Call(`_MCMCprecision_stationaryArma`, N, epsilon, sample, progress, digits)
}

stationaryArmaSparse <- function(N, epsilon = 0, sample = 5000L, progress = TRUE, digits = 8.) {
    .Call(`_MCMCprecision_stationaryArmaSparse`, N, epsilon, sample, progress, digits)
}

stationaryEigen <- function(N, epsilon = 0, sample = 5000L, progress = TRUE, digits = 8.) {
    .Call(`_MCMCprecision_stationaryEigen`, N, epsilon, sample, progress, digits)
}

stationary_reversible <- function(pi, N, abstol = 1e-5, maxit = 1e5L) {
    .Call(`_MCMCprecision_stationary_reversible`, pi, N, abstol, maxit)
}